33 results about "Service time" patented technology

The invention discloses a gas forklift, which comprise a forklift body and also comprises a gas tank, wherein the gas tank is arranged on a rear seat of the forklift body through a fixed support; the fixed support comprises a support frame and clamp rings; the clamp rings are formed by hinging two arc-shaped clamp arms; the end parts of one arc-shaped clamp arm is provided with a clamp splice; the clamp splice is provided with a through hole; the end part of the other arc-shaped clamp arms is hinged with an insertion; and each insertion is provided with an insertion rod which passes through the through hole and is locked by a nut. By adopting the structure, the gas forklift disclosed by the invention has the following advantages that 1, as the gas tank is installed on the rear seat of the forklift, the service time of the gas of the forklift can be prolonged, frequent gas filling is avoided, and the working efficiency is increased; 2, meanwhile, the gas tank is convenient in replacement, so that operation troubles brought by opening the rear seat of the forklift when gas filling is performed are avoided; and 3, the two arc-shaped clamp arms can be conveniently connected or loosened, therefore, not only is the gas tank fixed but also the gas tank can be conveniently replaced.

The invention includes a camera that captures an image of a user, a first estimation unit that estimates attributes of the user included in the image captured by the camera, an extraction unit that extracts candidates from among services corresponding to the estimated attributes on the basis of an availability status of each service time frame, and a display control unit that displays the extracted candidates on a display screen.

This application provides a network link capacity management method, apparatus, device, and medium, relating to the field of computer technology. The method includes: collecting link traffic of a network link; statistically analyzing the bandwidth utilization of the network link within a first period based on the link traffic and the link bandwidth of the network link, obtaining a first statistical bandwidth utilization rate corresponding to the first period, wherein the first period includes multiple service time periods; comparing the first statistical bandwidth utilization rate with a capacity expansion threshold; and if the first statistical bandwidth utilization rate is greater than the capacity expansion threshold, then expanding the link bandwidth of the network link. Thus, by using the statistical bandwidth utilization rate of the network link within a time period containing multiple service time periods as an evaluation indicator for whether network link capacity expansion is needed, the accuracy of capacity expansion judgment is improved, achieving economical and reliable management of network link capacity.

This invention relates to a method for evaluating service damage of aero-engine compressor blades, solving the problem that current blade performance testing cannot obtain test values ​​'d' through direct sampling from the blade. The method comprises the following steps: S1: Design the dimensions of the blade simulator; S2: Select a base material consistent with the blade; S3: Calculate the maximum temperature and maximum stress of the blade under different service conditions, based on the blade's design status; S4: Statistically count the number of Category I low-cycle cycles, Category III flight takeoff cycles, and Category IV powered takeoff cycles for at least 10 engines, and calculate the conversion factors for each type of cycle using the temperature and stress calculation values ​​under different service conditions to obtain the equivalent number of cycles for different service times; S5: Apply low-cycle fatigue loading, fixing and clamping the simulator, and performing low-cycle cyclic loading according to the stated temperature, stress, and number of cycles; S6: Take samples from the low-cycle fatigue-treated specimen and perform tensile and high-cycle fatigue mechanical property tests. This invention significantly reduces the need for collecting blade service conditions and parameters, greatly reducing workload.

This invention discloses a low-redundancy compressed data transmission method and apparatus for queuing and calling systems in the field of data transmission technology. The method includes: collecting single-service time series and queue waiting time series from multiple transmission endpoints connected to the cloud; extracting time features and inputting an adaptive timing window module to determine the timing window length; constructing endpoint state vectors and calculating state vector difference data; outputting prediction residual data through a lightweight prediction model, compressing the data, and outputting compressed encoded data; and performing redundancy difference analysis on the cloud side based on a preset redundancy level and updating the timing window length based on multiple redundancy differences. This invention solves the technical problem in existing technologies where a unified compression strategy cannot adapt to the differences in real-time waiting time perception between different transmission endpoints, leading to an inability to dynamically balance data redundancy and freshness. It achieves the technical effect of improving data transmission and compression efficiency while minimizing data redundancy.

The application discloses a kind of joint abnormality detection method and device for non-uniform multiple product service time series data, belong to time series abnormality detection field.The method processes the non-uniform time series data of each variable by time-aware dual-channel encoder, and the irregular sampling and missing value of observation value channel are handled by attenuation mechanism and input compensation, and the time interval channel learns event arrival mode;Subsequently, based on the hidden state representation of all variables, dynamically build variable relationship graph and use graph attention network to learn the dependence relationship between variables, update the hidden state and generate system-level joint representation vector;Finally, through joint abnormality detection module, based on reconstruction error and prediction error, system-level abnormality score and variable-level contribution degree are calculated, and abnormality detection and root cause analysis are realized.The application can effectively process non-uniform multiple time series data, accurately capture the dynamic dependence relationship between variables, play an important role in system monitoring and fault diagnosis in the fields of cloud computing, Internet of Things, etc., and has important application value.

This application discloses a service failure root cause analysis method and system based on cloud-edge collaboration. The cloud server-side method includes: receiving a standardized feature data stream sent by at least one edge node; the feature data stream is obtained by real-time collection and preprocessing of key performance data by the edge node, and the key performance data includes at least one of the following: abnormal SQL monitoring data, slow SQL performance data, and slow response interface data; performing cross-instance and cross-service time-series correlation analysis and pattern mining based on the feature data stream to determine each root cause node of the service failure phenomenon currently existing in the business system; constructing service failure information for each root cause node; and sending the service failure information to a visualization module on the client for user viewing. Using this application, the analysis blind spots caused by data silos and lack of correlation in traditional methods are solved, greatly improving the accuracy and global perspective of root cause location. At the same time, the automation of root cause analysis ensures the stability of the business system.

This application provides a method, apparatus, electronic device, and storage medium for calculating charter car prices. The method includes: acquiring a customized charter car order generated based on a user's multi-day travel request, and decomposing it into multiple independent sub-orders according to time and / or spatial dimensions; matching corresponding basic pricing rules based on the service time, geographical location, and additional costs of the sub-orders, and calculating multiple independent price influencing factors in parallel; accumulating the base price and floating premium to obtain the price of the sub-order; generating and storing pricing traceability information for the customized charter car order; and aggregating the prices of all sub-orders to generate a final quote for the customized charter car order. This application's embodiments, through the above method, solve the technical problems of opaque pricing processes and uncontrollable and difficult-to-trace price increases caused by the superposition of multiple factors in complex multi-temporal and spatial travel scenarios.

The application discloses a dynamic compensation method for full closed loop control of a grating ruler-based driver of a scriber, and comprises the following steps: realizing closed loop control positioning of the scriber through motor self-rotation encoder signals and grating ruler signals; long-term monitoring of position difference value data, comparison and analysis of data after grating ruler and rotation encoder failure with factory laser interferometer data to obtain changes of the scriber in service life; and dynamic compensation of precision and rigidity of the scriber. The application takes rotation encoders and grating rulers as main measuring devices, has higher data precision, realizes closed loop control, and improves the precision and reliability of the scriber; the dynamic compensation of precision and rigidity of the scriber can effectively prolong the service life of the scriber, and when the scriber approaches the designed service time and the precision deteriorates, the required precision can be effectively achieved.

The application provides a kind of based on multimodal context and speech enhancement information interaction processing method and system, the method comprises the following steps: S101, according to the preset service time configuration or operation instruction, trigger information interaction process;S102, based on information interaction process, access the multi-source data in current service period, generate structured data package;S103, construct dynamic bias list, in the decoding process of end-to-end automatic speech recognition model, log score is adjusted to addition bias mode, generate transcription text;S104, cross-modal reference resolution is carried out to transcription text, and structured service instruction is generated;S105, based on cross-modal reference resolution success rate and term misrecognition rate online update time-varying bias coefficient in addition bias mode;S106, closed-loop management and retrieval trace are carried out to structured data package and service instruction.The application solves the problem that professional term recognition is not accurate and spoken language reference is ambiguous, and improves the accuracy and efficiency of human-computer collaborative information processing in multiple scenarios.

The application discloses a micro-service time sequence prediction method based on multi-scale two-way fusion coding condition diffusion. First, a local segment of a micro-service key performance indicator and a time characteristic matrix thereof are acquired; local historical characteristics and global historical characteristics of the micro-service key performance indicator are extracted and fused to obtain historical fusion characteristics of the micro-service key performance indicator; then, a condition diffusion network is constructed, including a Transformer decoder, a gate linear unit and a characteristic linear modulation, and the historical fusion characteristics of the micro-service key performance indicator are taken as condition information of multi-head attention of the Transformer decoder; finally, based on multi-scale autoregressive diffusion, the condition diffusion network is used to gradually and reversely denoise the local segment of the micro-service key performance indicator at a prediction starting position, weighted fusion is performed on micro-service key performance indicator prediction results at various steps, and finally, micro-service key performance indicator prediction results are obtained. Through capturing local and global information and fully fusing, the prediction accuracy is improved.

The application relates to the technical field of equipment health management, and particularly relates to an equipment health management method based on cloud collaborative manufacturing. The method comprises a data acquisition module, which is arranged on equipment, is used for collecting various types of equipment state data in real time, and uploads the collected equipment state data to a cloud platform server; a data storage module, which is used for distributing each equipment to a corresponding equipment period group of a service stage according to service time length according to pre-stored equipment information, and storing the equipment state data to a state database of the corresponding equipment period group according to associated equipment information; a health analysis module, which is used for performing data mining on the equipment state data of the equipment period groups of different service stages, and respectively identifying the health states of each equipment of the equipment period groups of different stages; and an equipment portrait module, which is used for obtaining elite equipment groups of the equipment period groups of each service stage to perform historical data.

This invention relates to a load-balancing-based constellation communication-navigation coupled task scheduling method, belonging to the field of aerospace mission planning technology. It primarily improves resource allocation efficiency under equipment-level constraints and addresses the challenge of ensuring communication task completion while meeting the geometric accuracy requirements of navigation services. The invention uses satellite ephemeris data and mission requirement parameters as input to construct a multi-objective mixed integer linear programming (MILP) model. The optimal binary allocation variables are then obtained through a MILP solver, and the service satellites and service time slots for each mission are extracted to generate a scheduling table. This invention avoids the problem of navigation mission failure caused by communication tasks occupying multi-satellite convergence windows in separate planning. Simulations show that the overall mission completion rate is improved by an average of 12.3 percentage points, and the load variation coefficient is reduced by 66%–88%.

The application relates to the technical field of wireless communication, in particular to a high-throughput narrowband trunking communication system, method and electronic equipment. The application introduces a constant connection design, so that a terminal permanently stays on a dedicated service time slot allocated by a base station after completing initial registration on a control channel. When data needs to be transmitted, the terminal does not need to go through a complicated "application-response-switching" link establishment process, but can directly transmit data by detecting the idle state of the service time slot. This fundamental change eliminates the main overhead caused by signaling interaction, greatly improves the system throughput, significantly reduces the transmission delay, and maximally reduces the waste of air interface resources.

The application discloses a networking control method and system based on a low-orbit constellation, and mainly solves the problems of network architecture identity fragmentation, lack of global optimization of resource scheduling, and low beam coverage efficiency in the existing satellite-ground networking. The scheme comprises the following steps: an operation and maintenance center calculates the center point of a ground network based on the distribution of ground stations and the beam coverage radius; a network access satellite dynamically adjusts the beam pointing according to the ground network center point and the real-time position of the satellite itself, so that the beam center coincides with the ground network center point; the operation and maintenance center determines the effective service time window of each low-orbit satellite to each ground network according to the antenna tilt angle of the ground station; the low-orbit satellite searches for the ground network to be accessed according to the network access satellite plan and the broadcast message of the ground network master station, and determines the access protocol or the replacement protocol to be executed according to the network access satellite state information in the broadcast message of the ground network master station. The application can improve the beam coverage efficiency of the satellite beam to the ground network members, maximally reduce the satellite switching frequency, avoid the fragmentation of the low-orbit satellite network and the ground network at the network architecture level, and can be used in the scene of deep integration of the low-orbit satellite and the ground network.

An electronic device, according to one embodiment of the present disclosure, comprises: a communication circuit; a display; a memory storing instructions; and at least one processor, wherein the instructions, when executed individually or collectively by the at least one processor, may instruct the electronic device to: identify an orbital plane of a satellite that has entered a communicable area; determine, on the basis of the orbital plane, a service-available time for communication using the satellite; store an actual service time using the satellite; identify an inter-satellite gap time on the basis of the actual service time; and provide, via the display, schedule information of a non-terrestrial network service related to at least one of the determined service time, the actual service time, or the inter-satellite gap time.

This information processing device comprises: an acquisition unit that acquires a service plan of a transport, and a first index corresponding to a service time zone and a service section; a superimposition unit that superimposes and displays, on a display unit, a diagram image indicating the service plan and a heat map image indicating the first index; and an update unit that updates one or both of the diagram image and the heat map image in accordance with editing of the service plan based on a user operation.

The application relates to the field of satellite communication and discloses a network-aware data transmission method and device, computer equipment and a storage medium, the method comprising the following steps: acquiring the running state and network service time of all satellite nodes in a low-orbit satellite network; constructing a time-varying graph model based on all satellite nodes, the links between the satellite nodes and the network service time; calculating the link transmission capacity of each transmission link based on the time-varying graph model and the running state, performing maximum link transmission capacity routing for each time slot, and obtaining a data transmission scheme of the low-orbit satellite network. By implementing the application, the time-varying graph model is constructed considering that the satellite nodes in the low-orbit satellite network move at a high speed along an orbit over time, the link transmission capacity is calculated through the time-varying graph model to obtain the network topology of each time slot, and routing is performed. The method determines the data transmission link based on the time-varying graph model in consideration of the transmission capacity, improves the network load balancing capability, and enhances the transmission robustness.

A network handover processing method includes receiving service real-time requirement information from a network data analytics function (NWDAF) entity, the service real-time requirement information indicating a timeliness requirement of a service provided to user equipment and by a service provider, and the service real-time requirement information being generated by the NWDAF entity based on the service. The method also includes generating, based on the service real-time requirement information, a handover policy for an access network entity connected to the user equipment, and transmitting the handover policy to a session management function (SMF) entity to configure other network entities with the handover policy. The method further includes applying the handover policy by the access network entity during handover of the user equipment.

A scheduling method is provided for arranging target wake-up time communication between an access point and at least one site. The scheduling method includes the access point adjusting the broadcast target wake-up time schedule according to power-saving settings, and the access point transmitting the broadcast target wake-up time schedule. The broadcast target wake-up time schedule includes the broadcast target wake-up time start time, the broadcast target wake-up time service time, and the broadcast target wake-up time interval.

The application discloses a communication method, device, base station, movable relay and storage medium, and relates to the field of wireless communication. The specific implementation scheme is as follows: a base station acquires a first position where a movable relay is located and a second position where a terminal is located, and the terminal receives data from the base station through the movable relay; according to the energy efficiency of the movable relay, the first position of the movable relay and the second position of the terminal, the planning path information of the movable relay is determined, and the planning path information is sent to the movable relay. Therefore, the base station can determine the planning path information of the movable relay according to the energy efficiency of the movable relay, the position where the movable relay is located and the position where the terminal is located. Since the path planning information is determined in combination with the energy efficiency of the movable relay, the energy efficiency state of the movable relay can be fully considered, so that the movable relay moves according to the planning path information, the energy efficiency of the movable relay can be improved, and the communication service time of the movable relay can be prolonged.

The application discloses a multi-objective vehicle path optimization method based on fuzzy time window satisfaction degree, which is suitable for a distribution scene containing a distribution center, vehicles and customer sites. The method first acquires customer coordinates, demand, time window and other data and calculates a distance matrix, generates a disturbed time window after disturbance on the basis of random disturbance of the deterministic time window, and represents the disturbed time window as a three-parameter fuzzy number [a, m, b]. The fuzzy arrival and service time are obtained through fuzzy operator recursion. Then, a quasi-trapezoidal membership function is constructed to calculate customer satisfaction and average satisfaction through barycenter and similarity. A heuristic and roulette are used to generate an initial population, and a distribution cost Cost and average satisfaction AvgMu are used as double targets. After non-dominated sorting, tournament selection, crossover and mutation evolution, the solution quality is optimized by combining local search, and the Pareto optimal solution set is output after the termination condition is met. The application integrates the uncertainty of the time window into optimization, balances the cost and satisfaction, and improves the path robustness.

The application provides a pipeline inner wall corrosion state evaluation method and system, the method comprises the following steps: obtaining the corrosion type and specific service time of the pipeline inner wall to be evaluated; based on the corrosion type, a corresponding function relationship is obtained, the function relationship takes the service time of the pipeline as the independent variable and takes the self-corrosion current density of the pipeline as the dependent variable; based on the specific service time and the function relationship, the specific self-corrosion current density of the pipeline to be evaluated is calculated; the specific self-corrosion current density is compared with the preset maximum allowable self-corrosion current density, and the corrosion state of the pipeline to be evaluated is evaluated. It can be applied to the pipeline inner wall corrosion state evaluation of a specific corrosion type under a specific service time.

The application discloses a kind of intelligent scheduling methods, devices and equipment of service resource and storage medium, wherein the method comprises: receiving the service request submitted by user, and the service request at least includes service type, expected service time and special demand description;Dynamic demand urgency score of the service request is calculated based on multi-modal fusion model, including: extracting the multi-dimensional features associated with the service request, the multi-dimensional features at least include user portrait features, real-time environment features and order semantic features obtained by semantic analysis based on the special demand description;The multi-dimensional features are input into the pre-trained urgency evaluation model, and the quantitative dynamic demand urgency score is output;Real-time resource state of service area and future resource state predicted based on historical data are obtained, to form enhanced resource state view;Global scheduling decision is made based on reinforcement learning agent, to generate final scheduling sequence.

The application discloses a kind of water conservancy work condition data double-link automatic switching and transmission method and system, belong to data transmission technical field, its method specifically includes: collecting water conservancy work condition data, establishes main transmission link and backup transmission link, the work condition data frame is generated to the atomization encapsulation of water conservancy work condition data, real-time monitoring is carried out to main transmission link and backup transmission link, link performance parameter is obtained and link health degree index is formed, based on the link health degree index and data service time limit and fastness requirement, dynamically generate link switching criterion, when main transmission link meets link switching criterion, without interrupting the work condition data frame transmission in current sending queue, it is synchronously transmitted on backup transmission link, and when meeting takeover condition, switch to backup transmission link, and carry out work condition data frame transmission;The application reduces the data loss, repetition and disorder situation generated in switching process, and improves the adaptation ability to different types of water conservancy work condition data.

This invention discloses a vehicle routing optimization method integrating a large language model and a branch-and-price algorithm, comprising the following steps: Step S1, constructing a set partitioning model for the vehicle routing problem. This model is constructed based on a set of feasible vehicle routes, where each feasible route must satisfy constraints such as customer time window, demand, maximum vehicle service time, and load capacity. Under the premise of ensuring that each customer is visited and served only once, the model aims to minimize the total delivery cost, which includes the fixed usage cost of the vehicle and the related costs incurred by vehicle-drone collaborative delivery. Step S2, solving the set partitioning model using an exact algorithm integrating a large language model and branch-and-price to obtain the optimal vehicle collaborative delivery route.